A storage system typically comprises one or more storage devices into which information may be entered, and from which information may be obtained, as desired. The storage system includes a storage operating system that functionally organizes the system by, inter alia, invoking storage operations in support of a storage service implemented by the system. The storage system may be implemented in accordance with a variety of storage architectures including, but not limited to, a network-attached storage environment, a storage area network and a disk assembly directly attached to a client or host computer. The storage devices are typically disk drives organized as a disk array, wherein the term “disk” commonly describes a self-contained rotating magnetic media storage device. The term disk in this context is synonymous with hard disk drive (HDD) or direct access storage device (DASD).
Storage of information on the disk array is preferably implemented as one or more storage “volumes” of physical disks, defining an overall logical arrangement of disk space. The disks within a volume are typically organized as one or more groups, wherein each group may be operated as a Redundant Array of Independent (or Inexpensive) Disks (RAID). Most RAID implementations enhance the reliability/integrity of data storage through the redundant writing of data “stripes” across a given number of physical disks in the RAID group, and the appropriate storing of redundant information (parity) with respect to the striped data. The physical disks of each RAID group may include disks configured to store striped data (i.e., data disks) and disks configured to store parity for the data (i.e., parity disks). The parity may thereafter be retrieved to enable recovery of data lost when a disk fails. The term “RAID” and its various implementations are well-known and disclosed in A Case for Redundant Arrays of Inexpensive Disks (RAID), by D. A. Patterson, G. A. Gibson and R. H. Katz, Proceedings of the International Conference on Management of Data (SIGMOD), June 1988.
The storage operating system of the storage system may implement a high-level module, such as a file system, to logically organize the information stored on the disks as a hierarchical structure of directories, files and blocks. For example, each “on-disk” file may be implemented as set of data structures, i.e., disk blocks, configured to store information, such as the actual data for the file. These data blocks are organized within a volume block number (vbn) space that is maintained by the file system. The file system organizes the data blocks within the vbn space as a “logical volume”; each logical volume may be, although is not necessarily, associated with its own file system. The file system typically consists of a contiguous range of vbns from zero to n, for a file system of size n+1 blocks.
A known type of file system is a write-anywhere file system that does not overwrite data on disks. If a data block is retrieved (read) from disk into a memory of the storage system and “dirtied” (i.e., updated or modified) with new data, the data block is thereafter stored (written) to a new location on disk to optimize write performance. A write-anywhere file system may initially assume an optimal layout such that the data is substantially contiguously arranged on disks. The optimal disk layout results in efficient access operations, particularly for sequential read operations, directed to the disks. An example of a write-anywhere file system that is configured to operate on a storage system is the Write Anywhere File Layout (WAFL®) file system available from Network Appliance, Inc., Sunnyvale, Calif.
The storage operating system may further implement a storage module, such as a RAID system, that manages the storage and retrieval of the information to and from the disks in accordance with input/output (I/O) operations. The RAID system is also responsible for parity operations in the storage system. Note that the file system only “sees” the data disks within its vbn space; the parity disks are “hidden” from the file system and, thus, are only visible to the RAID system. The RAID system typically organizes the RAID groups into one large “physical” disk (i.e., a physical volume), such that the disk blocks are concatenated across all disks of all RAID groups. The logical volume maintained by the file system is then “disposed over” the physical volume maintained by the RAID system.
The storage system may be configured to operate according to a client/server model of information delivery to thereby allow many clients to access the directories, files and blocks stored on the system. In this model, the client may comprise an application, such as a database application, executing on a computer that “connects” to the storage system over a computer network, such as a point-to-point link, shared local area network, wide area network or virtual private network implemented over a public network, such as the Internet. Each client may request the services of the file system by issuing file system protocol messages (in the form of packets) to the storage system over the network. By supporting a plurality of file system protocols, such as the conventional Common Internet File System (CIFS) and the Network File System (NFS) protocols, the utility of the storage system is enhanced.
A noted disadvantage of conventional storage systems is that they typically retain a plurality of copies of the same data. For example, a memo may be distributed to all employees of a company via e-mail, thereby resulting in a copy of the memo being stored in each employee's e-mail directory. The storage of such duplicate data increases the total consumption of storage space utilized by the storage system and causes administrators to expand the physical storage space available for use by the system, thereby increasing total costs of maintaining the storage system.
One technique for achieving a reduction in data duplication (de-duplication) is described in U.S. Pat. No. 5,990,810, entitled METHOD FOR PARTITIONING A BLOCK OF DATA INTO BLOCKS AND FOR STORING AND COMMUNICATING SUCH SUBBLOCKS, by Ross Williams, issued Nov. 23, 1999 (hereafter “the '810 patent”). The method described in the '810 patent first utilizes a rolling hash function to generate a plurality of sub-blocks of data. The rolling hash utilizes a fixed size window of data that results in a boundary being placed between two subblocks. Once a block of data has been partitioned into sub-blocks, the hash value of each sub-block is calculated to form a table of hash values. The hash table is then used to determine if a new sub-block is identical to any sub-block whose hash value has previously been stored in the hash table. To perform this determination, the new sub-block's hash value is calculated and compared with the values contained in the hash table. If the new sub-block's hash value has been previously stored within the hash table, then the sub-block identified with the stored hash value is considered identical to the new sub-block. In such a case, the new sub-block is replaced with a pointer to the previously stored subblock, thereby reducing the amount of storage space required for the sub-block. A noted disadvantage of the technique described in the '810 patent is that it requires performance of an extensive number of computationally intensive hashing calculations, which may affect the overall performance of a storage system implementing such a method. Another noted disadvantage is that the hash table will become larger as the size of data set increases and may not scale to large data sets such as terabytes or petabytes of data.
Another technique for eliminating duplicate data is described in U.S. patent application Ser. No. 11/105,895, filed on Apr. 13, 2005 entitled METHOD AND APPARATUS FOR IDENTIFYING AND ELIMINATING DUPLICATE DATA BLOCKS AND SHARING DATA BLOCKS IN A STORAGE SYSTEM, by Ling Zheng, et al., the contents of which are hereby incorporated by reference. In the system described in this patent application, all data de-duplication operations are performed on fixed size blocks that are illustratively 4 kilobytes (KB) in size. When a new block is to be stored, a hash is computed of the 4 KB block and compared with a hash table containing hash values of previously stored blocks. Should the new block's hash value match the previously stored block, there is a high degree of probability that the new block is identical to the previously stored block. In such a case, the new block is replaced with a pointer to the previously stored block, thereby reducing storage resource consumption.
A third technique, as mentioned in DELTA STORAGE FOR ARBITRARY NONTEXT FILES by Chris Reichenberger, In Proceedings of the 3rd International Workshop on Software Configuration Management, Trondheim, Norway, 1214 June 1991 (June 1991), ACM, pp. 144-152, is to use the hashes of data to find the longest common data sequence.
However, a noted disadvantage of the above-described techniques is that they require that the data first be stored on a storage system before the data de-duplication process occurs. This requires that the storage system have sufficient storage space to store the data in an un-de-duplicated form. Furthermore, additional computations are required to perform the de-duplication while still servicing other data access requests, thereby increasing the overall processing load on the storage system. This results in reduced performance and increased latency for processing data access requests.